Highly Assisted Driving Platform

ABSTRACT

Methods for providing a highly assisted driving (HAD) service include: (a) transmitting telematics sensor data from a vehicle to a remote first server; (b) transmitting at least a portion of the telematics sensor data from the remote first server to a remote second server, wherein the remote second server is configured to execute a HAD application using received telematics sensor data, and wherein the HAD application is configured to output a HAD service result; and (c) transmitting the HAD service result from the remote second server to a client. Apparatuses for providing a HAD service are described.

TECHNICAL FIELD

The present teachings relate generally to Highly Assisted Driving (HAD),Advanced Driver Assistance Systems (ADAS), Advanced Traveler InformationSystems (ATIS), navigation systems, and the like.

BACKGROUND

Present day vehicles may be equipped with sensors to sense theirinternal and/or external environments. These sensors may be sampled atdifferent frequencies and a substantial amount of sensor data may becollected over a short period of time.

Driver assistance systems may use sensors to monitor a vehicle'senvironment and/or a driver's movements in order to provide a highlyassisted driving (HAD) service (e.g., early detection of potentiallydangerous situations, collision avoidance, etc.). In some instances, HADsystems may automatically intervene to avoid or at least minimize theseverity of an accident.

Different HAD applications (e.g., collision avoidance, lane departurewarning, etc.) may use different amounts, sample rates, and/or latenciesof sensor data. As a result, there is no inclusive platform on which allof the various HAD applications may be supported and, therefore, no wayto seamlessly integrate the various HAD applications in a vehicle.Instead, different platforms are typically used for the different HADapplications.

SUMMARY

The scope of the present invention is defined solely by the appendedclaims, and is not affected to any degree by the statements within thissummary.

By way of introduction, a method in accordance with the presentteachings includes: (a) transmitting, by a processor, telematics sensordata from a vehicle to a remote first server; (b) transmitting, by theprocessor, at least a portion of the telematics sensor data from theremote first server to a remote second server, wherein the remote secondserver is configured to execute a highly assisted driving (HAD)application using received telematics sensor data, and wherein the HADapplication is configured to output a HAD service result; and (c)transmitting, by the processor, the HAD service result from the remotesecond server to a client.

An apparatus in accordance with the present teachings includes at leastone processor and at least one memory including computer program codefor one or more programs. The at least one memory and the computerprogram code are configured to, with the at least one processor, causethe apparatus to perform at least the following: (a) transmit telematicssensor data from a vehicle to a remote first server; (b) transmit atleast a portion of the telematics sensor data from the remote firstserver to a remote second server, wherein the remote second server isconfigured to execute a highly assisted driving (HAD) application usingreceived telematics sensor data, and wherein the HAD application isconfigured to output a HAD service result; and (c) transmit the HADservice result from the remote second server to a client.

A non-transitory computer readable storage medium in accordance with thepresent teachings has stored therein data representing instructionsexecutable by a programmed processor. The storage medium includesinstructions for (a) transmitting telematics sensor data from a vehicleto a remote first server; (b) transmitting at least a portion of thetelematics sensor data from the remote first server to a remote secondserver, wherein the remote second server is configured to execute ahighly assisted driving (HAD) application using received telematicssensor data, and wherein the HAD application is configured to output aHAD service result; and (c) transmitting the HAD service result from theremote second server to a client.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a flow chart of an exemplary process for providing a highlyassisted driving (HAD) service.

FIG. 2 shows an exemplary architecture of a system for providing a HADservice in accordance with the present teachings.

FIG. 3 shows a schematic illustration of exemplary relationships betweensystem components in an exemplary architecture in accordance with thepresent teachings.

FIG. 4 shows a block diagram of a representative apparatus 400 inaccordance with the present teachings for providing a HAD service.

FIG. 5 shows a representative general computer system 500 for use withan apparatus in accordance with the present teachings.

DETAILED DESCRIPTION

A generic framework or platform configured to support a plurality of HADapplications has been discovered and is described herein. In accordancewith the present teachings, these HAD applications may be created,executed, modified, integrated, and/or the like in a vehicle. In someembodiments, as further described herein, an architecture in accordancewith the present teachings may be used to support HAD applicationsincluding but not limited to collision avoidance, early warning systems,autonomous driving, personalized autonomous driving, cruise control,lane change warning systems, an automobile app store, telematics sensoranalytics, and/or the like, and combinations thereof. In someembodiments, an architecture in accordance with the present teachings iscloud-based.

In addition to being configured to support a plurality of HADapplications, an architecture in accordance with the present teachingsmay, in some embodiments, be further configured to achieve one or moreof the following: preserve a driver's privacy; avoid overwhelming awireless link to a cloud-based storage system with useless telematicssensor data; facilitate sharing of telematics sensor analysis resultsbetween vehicles; permit data sharing between a plurality of HADapplications since the applications are running on a common platform;facilitate seamless communication of vehicles; allow vehicles withmissing or broken sensors to piggyback on sensor data harvested from aneighboring vehicle (e.g., an older-model vehicle lacking a given sensormay still exploit the corresponding sensor data via a newer-modelversion of the vehicle proximal thereto); prevent overwhelming of theprocessing power and memory of a vehicle by telematics sensor data;and/or support vehicles from more than one brand of original equipmentmanufacturer (OEM).

Throughout this description and in the appended claims, the followingdefinitions are to be understood:

As used herein, the phrase “automotive cloud” refers to a cloud-basedstorage system. In some embodiments, a cloud-based storage systemincludes one or a plurality of remote servers. In some embodiments, acloud-based storage system is configured for receiving data from one ora plurality of vehicles, transmitting data to one or a plurality ofvehicles, transmitting data to one or a plurality of differentcloud-based storage systems, and/or receiving data from one or aplurality of different cloud-based storage systems. In some embodiments,the transmitting and/or receiving of data between vehicles and/orservers may be achieved wirelessly.

As used herein, the phrase “personalized driving” refers to aconfiguration of an autonomous vehicle wherein the vehicle may drive ina style that mimics the idiosyncratic driving style of a specificindividual (e.g., “Bob,” “Mary,” etc.) and/or a stereotypical drivingstyle associated with a hypothetical generic driver (e.g., a “cautious”driver, an “impatient” driver, a driver transporting breakable cargo, anambulance driver, a police officer, etc.).

It is to be understood that elements and features of the variousrepresentative embodiments described below may be combined in differentways to produce new embodiments that likewise fall within the scope ofthe present teachings.

By way of general introduction, a method for providing a highly assisteddriving (HAD) service in accordance with the present teachings includes:(a) transmitting telematics sensor data from a vehicle to a remote firstserver; (b) transmitting at least a portion of the telematics sensordata from the remote first server to a remote second server; and (c)transmitting a HAD service result from the remote second server to aclient. The remote second server is configured to execute a HADapplication using received telematics sensor data, and the HADapplication is configured to output the HAD service result.

The type of HAD application executed by the remote second server is notrestricted and includes all manner of current and yet-to-be-developedHAD services that may be configured to accept telematics sensor data asan input. By way of example, representative HAD applications inaccordance with the present teachings include but are not limited toautonomous driving, personalized driving of autonomous vehicles,in-vehicle navigation systems, adaptive cruise control (ACC), earlywarning systems, adverse weather conditions warning systems, lanedeparture warning systems, collision warning systems, lane changeassistance, collision avoidance system (e.g., pre-crash system),intelligent speed adaptation or intelligent speed advice (ISA), nightvision, adaptive light control, pedestrian protection system, automaticparking, traffic sign recognition, blind spot detection, driverdrowsiness detection, vehicular communication systems, hill descentcontrol, electric vehicle warning sounds used in hybrids and plug-inelectric vehicles, telematics sensor analytics, automobile app stores,and/or the like, and combinations thereof.

In some embodiments, each of the vehicle, the remote first server, theremote second server, and the client is independently configured forwireless communication. In some embodiments, the transmitting of thetelematics sensor data from the vehicle to the remote first serveroccurs via wireless communication. In some embodiments, the transmittingof at least the portion of the telematics sensor data from the remotefirst server to the remote second server occurs via wirelesscommunication. In some embodiments, the transmitting of the HAD serviceresult from the remote second server to the user occurs via wirelesscommunication. In some embodiments, each of the transmitting of thetelematics sensor data from the vehicle to the remote first server, thetransmitting of at least the portion of the telematics sensor data fromthe remote first server to the remote second server, and thetransmitting of the HAD service result from the remote second server tothe user occurs via wireless communication.

In some embodiments, the remote first server and the remote secondserver are controlled by separate entities. By way of example, in someembodiments, the remote first server may be controlled by an OEM (e.g.,a vehicle manufacturer), and the remote second server may be controlledby a HAD service provider. In some embodiments, the HAD service provideris Nokia (e.g., HERE).

In some embodiments, the telematics sensor data are acquired from one ora plurality of telematics sensors onboard a vehicle. Telematic sensorsmay be provided externally and/or internally on the vehicle.Representative telematics sensors for use in accordance with the presentteachings include but are not limited to differential GPS (a.k.a.D-GPS), windshield wiping sensors, laser sensors, light sensors, camerasensors, microphone sensors, shift sensors, pedal sensors, leversensors, brake sensors, speed sensors, acceleration sensors, headlampsensors, steering wheel sensors, and/or the like, and combinationsthereof.

In some embodiments, a method in accordance with the present teachingsfurther includes collecting the telematics sensor data in a vehicle datacollector onboard the vehicle. By way of example, in some embodiments,the vehicle data collector is provided as an onboard computer configuredfor storing and optionally processing telematics sensor data generatedon the vehicle prior to the transmission of such data to the remotefirst server.

In some embodiments, a method in accordance with the present teachingsfurther includes pre-processing at least a portion of the telematicssensor data prior to transmitting the telematics sensor data to theremote first server. In some embodiments, at least a portion of thepre-processing is performed onboard the vehicle (e.g., in the vehicledata collector). The nature of the pre-processing performed on collectedtelematics sensor data is not restricted and, in some embodiments,representative types of pre-processing may include but are not limitedto data filtering (e.g., removing out-of-range sensor data, checkingdata against previously cached data for duplicates and/or redundancies,and/or the like), data anonymization (e.g., to protect driver privacyregarding identity, vehicle location, and/or the like), datacompression, data enveloping, and/or the like, and combinations thereof.

In some embodiments, a method in accordance with the present teachingsfurther includes determining whether the telematics sensor datatransmitted from the vehicle to the remote first server satisfy apredefined latency threshold. In some embodiments, a method inaccordance with the present teachings further includes determiningwhether at least the portion of the telematics sensor data transmittedto the remote second server satisfies a predefined latency thresholdprior to using the received telematics sensor data as an input in theHAD application. In some embodiments, a method in accordance with thepresent teachings further includes determining whether the telematicssensor data transmitted from the vehicle to the remote first serversatisfy a predefined first latency threshold, and determining whether atleast the portion of the telematics sensor data transmitted from theremote first server to the remote second server satisfies a predefinedsecond latency threshold. In some embodiments, the first latencythreshold and the second latency threshold are the same. In otherembodiments, the first latency threshold and the second latencythreshold are different.

In some embodiments, a method in accordance with the present teachingsfurther includes transmitting additional telematics sensor data from aneighboring vehicle (e.g., in some embodiments, a plurality ofneighboring vehicles) to the remote first server. In some embodiments, amethod in accordance with the present teachings further includestransmitting additional telematics sensor data from a neighboringvehicle (e.g., in some embodiments, a plurality of neighboring vehicles)to the remote second server. In some embodiments, a method in accordancewith the present teachings further includes transmitting additionaltelematics sensor data from a first neighboring vehicle (e.g., in someembodiments, a plurality of first neighboring vehicles) to the remotefirst sever, and transmitting additional telematics sensor data from asecond neighboring vehicle (e.g., in some embodiments, a plurality ofsecond neighboring vehicles) to the remote second server. In someembodiments, the first neighboring vehicle (or plurality thereof) andthe second neighboring vehicle (or plurality thereof) are the same. Inother embodiments, the first neighboring vehicle and the secondneighboring vehicle are different.

The collection of additional telematics sensor data from one or aplurality of neighboring vehicles may provide a crowd-sourced heuristicby which to corroborate and/or prune telematics sensor data from aprimary vehicle (e.g., a vehicle that transmitted telematics sensor datato the remote first server or a vehicle that receives a HAD serviceresult from the remote second server). In some embodiments, crowdsourcing from one or more neighboring vehicles facilitates theseparation of true events and/or updates from vehicle-centric “falsepositives.” Thus, in some embodiments, a method in accordance with thepresent teachings further includes corroborating at least the portion ofthe telematics sensor data transmitted to the remote second server viacomparison and/or combination with additional telematics sensor dataacquired from one or a plurality of neighboring vehicles.

As used herein the term “client” refers broadly to any type of mobiledevice (e.g., a vehicle and/or a component thereof, including but notlimited to a navigation systems, an onboard computer, etc.; a mobilephone; and/or the like). In some embodiments, the mobile device isconfigured to be under at least partial manual control by a human user(e.g., a vehicle that is configured to receive one or a plurality of HADservices from a remote server). In other embodiments, the mobile deviceincludes an autonomously driven vehicle that may or may not include anyhuman passenger. In some embodiments, the term “client” includes a fleet(e.g., a plurality) of mobile devices each of which is configured toreceive the HAD service result. In some embodiments, the client isconfigured to make an operational adjustment based on receipt of the HADservice result (e.g., an autonomously driven vehicle that makes a courseadjustment based on receipt of a warning that a road obstruction liesahead on the present course).

FIG. 1 shows a flow chart of a representative method 100 for providing aHAD service in accordance with the present teachings. As shown in FIG.1, the method 100 begins at block 102 and may include collecting 104telematics sensor data (TSD) in a vehicle data collector. The collectedTSD may optionally be pre-processed as shown at block 106 and, in someembodiments, the pre-processing may take place onboard the vehicle(e.g., in the vehicle data collector). In some embodiments, thepre-processing includes anonymization of the data.

As shown at block 108 in FIG. 1, the optionally pre-processed data maybe transmitted to a remote first server which, in some embodiments, iscontrolled by a OEM (e.g., a vehicle manufacturer). As shown at block110, the TSD—or a least a portion thereof—may be transmitted to a remotesecond server which, in some embodiments, is controlled by a HAD serviceprovider. At decision block 112, a determination may be made as towhether or not the TSD satisfy a pre-defined latency threshold. If it isdetermined that the TSD do not satisfy the latency threshold, the TSDare not used in a subsequent HAD application as shown at block 114.However, if the TSD do satisfy the latency threshold, the TSD may thenbe used in a HAD application as shown at block 116. The HAD serviceresult generated by executing a HAD application is transmitted to aclient as shown at block 118.

It is to be understood that the relative ordering of some acts shown inthe flow chart of FIG. 1 is meant to be merely representative ratherthan limiting, and that alternative sequences may be followed. Moreover,it is likewise to be understood that additional, different, or feweracts may be provided, and that two or more of these acts may occursequentially, substantially contemporaneously, and/or in alternativeorders. By way of example, the method shown in FIG. 1 may includeadditional acts including but not limited to collecting additional TSDfrom neighboring vehicles and/or corroborating at least the portion ofthe TSD via comparison and/or combination with additional telematicssensor data acquired from one or a plurality of neighboring vehicles. Inaddition, in some embodiments, a further determination as to whether alatency threshold has been satisfied (e.g., a second decision blockanalogous to decision block 112) may also be included in the process 100(e.g., in some embodiments, interposed between acts 108 and 110).

In some embodiments, a method in accordance with the present teachingsfor providing a HAD service is implemented using a computer and, in someembodiments, one or a plurality of the above-described acts areperformed by one or a plurality of processors. In some embodiments, oneor more of the one or the plurality of processors include graphicsprocessing units (GPUs). In other embodiments, one or more of the one orthe plurality of processors include central processing units (CPUs). Insome embodiments, methods in accordance with the present teachings areimplemented entirely on GPUs. In some embodiments, GPUs provide improvedand/or faster performance.

In some embodiments, as described above, the present teachings providemethods for providing a HAD service. In other embodiments, as furtherdescribed below, the present teachings also provide apparatuses forproviding a HAD service.

FIG. 4 shows a block diagram of a representative apparatus 400 inaccordance with the present teachings for providing a highly assisteddriving HAD service. In some embodiments, as shown in FIG. 4, anapparatus 400 in accordance with the present teachings is implemented aspart of a GPU in a computer system. In other embodiments, the apparatus400 may be implemented as part of a CPU in a computer system.

In some embodiments, as shown in FIG. 4, the apparatus 400 may include:a processor 402; a non-transitory memory 404 coupled with the processor402; first logic 406 stored in the non-transitory memory 404 andexecutable by the processor 402 to cause the apparatus 400 to transmittelematics sensor data (TSD) from a vehicle to a remote first server;second logic 408 stored in the non-transitory memory 404 and executableby the processor 402 to cause the apparatus 400 to transmit at least aportion of the telematics sensor data from the remote first server to aremote second server; and third logic 410 stored in the non-transitorymemory 404 and executable by the processor 402 to cause the apparatus400 to transmit an HAD service result from the remote second server to aclient (e.g., a vehicle).

In some embodiments, the apparatus 400 may further include one or moreof the following: fourth logic 412 stored in the non-transitory memory404 and executable by the processor 402 to cause the apparatus 400 tocollect the telematics sensor data in a vehicle data collector onboardthe vehicle; fifth logic 414 stored in the non-transitory memory 404 andexecutable by the processor 402 to cause the apparatus 400 topre-process at least a portion of the telematics sensor data in thevehicle data collector; sixth logic 416 stored in the non-transitorymemory 404 and executable by the processor 402 to cause the apparatus400 to transmit additional telematics sensor data from a neighboringvehicle to the remote first server; seventh logic 418 stored in thenon-transitory memory 404 and executable by the processor 402 to causethe apparatus 400 to determine whether at least the portion of thetelematics sensor data transmitted to the remote second server satisfiesa predefined latency threshold; and/or eighth logic 420 stored in thenon-transitory memory 404 and executable by the processor 402 to causethe apparatus 400 to corroborate at least the portion of the telematicssensor data transmitted to the remote second server via comparisonand/or combination with additional telematics sensor data acquired fromone or a plurality of neighboring vehicles.

In some embodiments, the apparatus 400 is configured as a deviceselected from the group consisting of navigation systems, mobile phones,personal computers, game consoles, laptops, notebooks, tablets, portablemedia players, personal digital assistants, pagers, and the like, andcombinations thereof. In some embodiments, the apparatus 400 isconfigured as a navigation system and/or a mobile phone and furtherincludes: (a) user interface circuitry and user interface softwareconfigured to (i) facilitate user control of at least some functions ofthe navigation system and/or mobile phone though use of a display and(ii) respond to user inputs; and (b) a display and display circuitryconfigured to display at least a portion of a user interface of thenavigation system and/or mobile phone, the display and the displaycircuitry configured to facilitate user control of at least some of thefunctions of the navigation system and/or mobile phone.

A non-transitory computer-readable storage medium in accordance with thepresent teachings has stored therein data representing instructionsexecutable by a programmed processor for providing a highly assisteddriving HAD service. The storage medium includes instructions for: (a)transmitting telematics sensor data from a vehicle to a remote firstserver; (b) transmitting at least a portion of the telematics sensordata from the remote first server to a remote second server, wherein theremote second server is configured to execute a HAD application usingreceived telematics sensor data, and wherein the HAD application isconfigured to output a HAD service result; and (c) transmitting the HADservice result from the remote second server to a user.

The following description and representative implementations illustratefeatures in accordance with the present teachings, and are providedsolely by way of illustration. They are not intended to limit the scopeof the appended claims or their equivalents.

In some embodiments, the sensor data emanating from vehicles may bearchived and/or processed on the vehicle itself. In other embodiments,the sensor data may be archived and/or processed in an automotive cloud(e.g., in a HAD service provider's cloud). In some embodiments, thearchiving and processing may take place on both the vehicle itself andin one or a plurality of automotive clouds.

Processing and archiving the sensor data on the vehicle itself maystrain the vehicle's resources (e.g., CPU processing power and/ormemory). On the other hand, if all of the sensor data are sent to theautomotive cloud, the bandwidth of the wireless service providers may beoverwhelmed, which can be costly. Accordingly, in some embodiments, theTSD may be compressed before transmission. In addition or alternatively,in some embodiments, the TSD may be filtered in order to weed outunnecessary and/or low quality data on the vehicle, such that only thehigh quality data are transmitted to the cloud. In some embodiments, acombination of both in-car data processing and automotive cloudprocessing is performed. By way of example, in some embodiments,processing that relates to critical decisions (e.g., imminent accidentwarnings) may be performed on the vehicle. Other processing associatedwith decisions that do not require immediate reactions and that involvelonger event horizons (e.g., based on adverse weather conditionswarnings a few miles down the road) may be performed in the cloud.

In some embodiments, combining sensor information from co-located (e.g.,neighboring) vehicles may increase confidence levels of the derived HADservice results (e.g., warnings about dangerous driving conditionsand/or collision avoidance). Direct communication between vehicles isknown as vehicle-to-vehicle (V2V) communication. Communication betweenvehicles via external clouds is known as vehicle-to-infrastructure (V2I)communication. In some embodiments, V2I communication may be used as amechanism of communication in autonomous driving (e.g., forcommunication between connected cars and a computer cloud). For example,if multiple vehicles detect adverse weather conditions in a certainregion (e.g., heavy rain, icy roads, and/or the like), other vehiclesapproaching the region may be informed of the adverse weather conditionsby continuously communicating with the automotive cloud.

In accordance with the present teachings, driver privacy may beprotected. By way of example, in some embodiments, privacy concerns maybe addressed by using a plurality of remote servers (e.g., two or moreautomotive clouds). In some embodiments of a multi-cloud system, thepersonal details of the driver and/or identifying information relatingto the vehicle and/or its location may be addressed at the OEM level.For example, the data may first be anonymized (e.g., on the vehicle) andthen sent to the OEM's server and/or sent to the OEM server and thenanonymized there. Subsequently, the sanitized data may be forwarded to aHAD service provider's cloud (e.g., HERE automotive cloud).

In accordance with the present teachings, data sharing between differentOEMs may be achieved. For example, data from a vehicle manufactured by afirst OEM and data from a vehicle manufactured by a second OEM may bothbe archived in a HAD service provider's automotive cloud. By executing aHAD application, (e.g., collision warning, personalized driving, cruisecontrol, and/or the like), telematics sensor analytics from the firstOEM may be used to trigger behaviors on a vehicle manufactured by thesecond OEM. Since different HAD applications may require differentgranularities and/or different frequencies of sensor data, a HADplatform of a type described herein may be used to support the variousapplications.

FIG. 2 shows an exemplary architecture 200 of a system for providing aHAD service in accordance with the present teachings. FIG. 2 depictsrepresentative subsystems of the architecture 200 and theirconnectivities. As shown in FIG. 2, the architecture 200 includes tworemote servers (e.g., clouds) in communication with one another and witha vehicle 201. The two remote servers include OEM cloud 202 and HADservice provider cloud 204 (e.g., HERE). Representative elements andacts that are controlled by and/or associated with the OEM cloud 202 areshown in FIG. 2 using light shading. In some embodiments, as shown inFIG. 2, the OEM-controlled elements and acts include a cloud datareceiver 206, an onboard database 208, a controller area network (CAN)bus 210, and a vehicle data collector 212.

Representative elements and acts that are controlled by and/orassociated with the HAD service provider cloud 204 are shown in FIG. 2using dark shading. In some embodiments, as shown in FIG. 2, the HADservice provider-controlled elements and acts include a HD map 214, areal time data processor 216, a persistent repository 218, a real timedata collector 220, a location cast part 222, and a content creationpart 224.

Information may be hidden from a vehicle's one or more sensors due toobstacles along a sensor's line of sight. By way of example, apedestrian may be hidden from view at an intersection and/or a trafficsign may be hidden by a large vehicle in front of the one or moresensors. In such situations, the vehicle from which information ishidden may rely on sensor data from one or more other vehicles ahead ofit that already submitted data to the automotive cloud. However, in somecases, front vehicle information may not be available. For example, evenif there are no obstacles along a sensor's line of sight, the sensorsmay be limited in range and, therefore, may be unable to accuratelyreport long-range data. As a result, the vehicle's ability to plan aheadmay be limited. To address this issue, as shown in FIG. 2, theautomotive cloud 204 may provide detailed HERE 3D maps, trafficinformation, dynamic content (e.g., parking availability, low-price gasstations, points of interest along a route, and/or the like), incidentinformation, and/or the like to vehicles connected to the cloud 204,thereby extending the sensor spatial range of those vehicles.

As described above, the architecture 200 shown in FIG. 2 involves an OEMand a HAD service provider. Original equipment manufacturers may lackthe resources to build and maintain large automotive clouds and to buildthe mathematical models used for sensor data fusion and HAD serviceresult predictions (e.g., road conditions). As a result, OEMs may notprovide HAD services themselves. Since the OEM may not have accurate 3Dmaps to be used, for example, in HAD applications, the OEM may be sendits data to a third party service provider (e.g., HERE) to build HADservices on its behalf.

By way of example, as shown in FIG. 2, vehicle data may be initiallycontrolled by the OEM. The vehicle data generated may be collected bythe vehicle data collector 212 onboard the vehicle 201. The vehicle datacollector 212 may be configured to perform basic TSD filtering. Forexample, duplicate and/or out-of-range sensor data may be suppressed bythe vehicle data collector 212. As a result of this suppression,unwanted and corrupted data are not sent to the clouds.

Various types of data filtering and preprocessing schemes may beemployed in accordance with the present teachings. For example, in someembodiments, predefined ranges may be stored on the vehicle 201. Whensensor data go beyond the stored predefined ranges, then that sensordata may be pruned. For example, if a stored predefined range oflatitude values is between 0 and 90, latitude values greater than 90 andless than 0 obtained from a D-GPS telematics sensor may be filtered. Insome embodiments, all sensor data may be temporarily cached for apredefined period of time in the onboard database 208 of the vehicle201. New TSD may be checked against previously cached data forduplicates and/or redundancies.

In the representative architecture 200 shown in FIG. 2, data from thevehicle data collector 212 may be sent to the OEM cloud 202. In someembodiments, a secure wireless communication line may be providedbetween the vehicle 201 and the OEM cloud 202. After preprocessing(e.g., in the vehicle data collector 212), as further described below,the TSD may be anonymized, compressed, and/or enveloped beforetransmission to the OEM cloud 202.

An anonymization process may be used to protect driver privacy includingbut not limited to personal information (e.g., name, age, address, phonenumber, and/or the like), exact location (e.g., at home, at a doctor'soffice, at a rehab center, and/or the like). All manner of anonymizationschemes are contemplated for use in accordance with the presentteachings, including but not limited to k-anonymity.

Compression is a bandwidth conservation scheme that may be used toreduce the size of the TSD before putting the data over thecommunication link. All manner of compression or archiving schemes arecontemplated for use in accordance with the present teachings, includingbut not limited to zipping. In some embodiments, compression may be usedin connection with driverless cars, which may produce large amounts ofdata (e.g., 1 Gb/s of data).

Enveloping may be used convert the TSD to an understandable format tofacilitate processing by the OEM and/or the HAD service provider.

The TSD may be transferred from the OEM cloud 202 to the HAD serviceprovider cloud 204. Various techniques may be used to handle latencyissues for transferring data from the vehicle 201 to the OEM cloud 202and/or from the OEM cloud 202 to the HAD service provider cloud 204. Insome embodiments, TSD latency thresholds may be predefined for each HADservice (e.g. automatic wiper blade activation). For example, if thelatency threshold is defined to be less than or equal to 30 seconds,sensor data that is older than 30 seconds may not be used as an input inan HAD application (e.g., determining whether or not to activate theautomatic wiper blades). To determine if a threshold has been breached,the latency threshold, current time, and timestamp of the TSD receivedin the HAD service provider cloud 204 may be checked before the data areused to output a HAD service result.

As further described below in reference to FIG. 3, different pathwaysmay be followed once the data arrive in the HAD service provider cloud204. FIG. 3 shows a schematic illustration of exemplary relationshipsand data flow pathways that may exist between representative systemcomponents and acts in an end-to-end (E2E) cloud-based architecture 300in accordance with the present teachings. In some embodiments, thearchitecture 300 implements three closed loops to support delivery ofHAD services from the HAD service provider cloud 304 to a fleet ofclients (e.g., vehicles). The three representative loops shown in FIG. 3correspond to three assisted driving domains. More specifically, loop 1corresponds to real world reference data (e.g., from a 3D map), loop 2corresponds to real time environmental data indicative of a status of anenvironment of the vehicle (e.g., weather, traffic, incidents, and/orthe like), and loop 4 corresponds to personalized driving.

Each of loops 1, 2, and 4 begins at vehicle data collector 312. Thevehicle data collector 312 is configured to collect sensor data, toextract observed events to the extent possible onboard the vehicle, andto send information to the automotive cloud. In some embodiments, thedata may first be sent to the OEM cloud 202 as shown in FIG. 2. As shownin FIG. 3, the data may be collected by the real time data collector 320and sent to the real time data processor 316. In addition, the data maybe stored in the persistent repository 318.

In loop 1 shown in FIG. 3, the real time data processor 316 may beconfigured to extract map updates from the incoming telematics sensorstream applying crowd-sourced heuristics and rules, and to send theextracted map updates to the high definition 3D map 314. For example, ifthe vehicle 301 determines that the real road is not well described bythe map, a map update message may be triggered and the map may beupdated using the route of the vehicle and, possibly, the routes ofother vehicles that have observed the same deviations of the map fromthe real road. The map 314 may validate and/or apply the updates,publish the updates, and/or broadcast notifications to the vehiclesthrough the location cast part 322.

The relevant map updates may be received in a requesting vehicle in acloud data receiver 326. The onboard map data repository of the vehicle301 is updated and may be used in defining driving strategy 328. As usedherein the, term “relevant” as used in reference to map updatessignifies that a vehicle may update a map in only a region thatcorresponds to its current location. By way of example, updates in SouthAmerica may not be effected by vehicles in Europe. Similarly, by way offurther example, map updates in Germany would not be taken by a car thatnever leaves France. In some embodiments, algorithms may be developedthat determine what “relevant” means in a given situation. For example,the location history of a vehicle may be analyzed to provide avehicle-specific “relevant area” that may be stored in the vehicleand/or in an automotive cloud depending on the vehicle's computingresources and/or other factors. Thus, updates in the “relevant area” maybe taken with first priority. As the vehicle drives to new locations,the “relevant area” may expand in response. In some embodiments, updatepriority may be determined based on factors such as time,memory/storage, and computer processing resources available on thevehicle, and/or the like, and combinations thereof.

In loop 2 shown in FIG. 3, the real time data processor 316 isconfigured to extract dynamic events from the incoming stream. As usedherein, the phrase “dynamic events” describes events such as traffic,incidents, weather, and/or the like, and combinations thereof. In someembodiments, the categorization of an event as being dynamic as opposedto static may be based on crowd-sourced heuristics and rules. Forexample, an incident may be determined with confidence based on thenumber of other vehicles reporting the incident. In some embodiments,the real time data processor 316 is further configured to refine otherdynamic information (e.g., traffic flow, incidents, weather, and/or thelike), fuse the other dynamic information with the extracted dynamicevents, and send information to the vehicles with low latency throughthe location cast part 322. In some embodiments, only potentiallyaffected vehicles receive the information.

In loop 4 shown in FIG. 3, data about the applications (e.g., personaldriving styles, collision avoidance data, and/or other vehicleapplications) may be accumulated in a persistent repository 318 andused, for example, by OEM analytics to identify appropriate adjustmentsto the driving strategy 328. These adjustments may periodically berefined and loaded to the vehicle 301.

In some embodiments, the HAD service provider cloud 304 implements aplatform as a service for partners of the HAD service provider. Theplatform may support a clear and logical separation of proprietaryinformation streams, data layers, and/or processing modules in each ofthe major system components (e.g., in FIG. 3, light shading correspondsto the OEM and dark shading corresponds to the HAD service provider).

Road situations may be complex. Even for a relatively simple scenariosuch as determining a Variable Speed Sign (VSS) at the lane level,complexities may develop. For example, the reported VSS value may varysignificantly depending on factors such as the position of a reportingvehicle, temporary or permanent obstacles that obstruct observation(e.g., trucks, trees, blind spots, and/or the like), positioning systemaccuracy, sophistication of the sensor vehicle instrumentation, and/orthe like, and combinations thereof. Thus, the system collecting dataacross the fleet may apply data fusion and/or crowd-sourcing techniquesto determine the values with the highest possible confidence.

The real time data processor 316 shown in FIG. 3 may serve as aconfidence-building engine configured to identify and increaseconfidence in a discovered event. In some embodiments, as furtherdescribed below, a real time data processor may implement at least thefollowing processes: (1) implement sensor fusion algorithms; (2) applycrowd-sourced rules; and (3) fuse discovered dynamic events with otherdynamic content.

Sensor fusion algorithms for the data coming from a particular vehiclemay be implemented by a real time data processor. The observed eventsmay be extracted with a computed confidence available at the vehiclelevel. By way of example, the observed event may include low visibilitydue to fog. The vehicle's right camera reports the presence of a VSS 200meters ahead with 50% probability. However, the VSS is not in the map.The vehicle's left camera, on the other hand, reports the VSS 250 metersahead with 75% probability. Statistical algorithms fuse information fromthe right camera and the left camera to report a VSS 240 meters aheadwith 85% probability. Similar algorithms may be applied to reportedspeeds and/or the like.

Crowd-sourced rules may be applied across a subset of the fleet based onlocation. The application of these rules may help to separate trueevents and/or updates from vehicle-centric “false positives.” By way ofexample, the deviation of a car trajectory from the map may be due tothe map being out-of-date, construction in the area altering the trafficflow, congestion forcing cars to drive on a shoulder, and/or the like.Thus, confirmation from multiple vehicles may be a prerequisite totriggering a map update. At this stage, the discovered map updates maybe delivered to the map engine for application.

The discovered dynamic events may be fused with other dynamic content(e.g., weather data from sensors of other vehicles) to further increaseconfidence levels and deliver the results to the fleet. For example, thecombination of information from a first vehicle reporting slippery/icyroads and information from a second vehicle reporting multipleengagements of an ABS is indicative of a conclusion of dangerous drivingconditions.

One skilled in the art will appreciate that one or more modules or logicdescribed herein may be implemented using, among other things, atangible computer-readable medium comprising computer-executableinstructions (e.g., executable software code). Alternatively, modulesmay be implemented as software code, firmware code, hardware, and/or acombination of the aforementioned.

FIG. 5 depicts an illustrative embodiment of a general computer system500. The computer system 500 can include a set of instructions that canbe executed to cause the computer system 500 to perform any one or moreof the methods or computer based functions disclosed herein. Thecomputer system 500 may operate as a standalone device or may beconnected (e.g., using a network) to other computer systems orperipheral devices. Any of the components discussed above, such as theprocessor, may be a computer system 500 or a component in the computersystem 500. The computer system 500 may implement a HAD module forproviding a highly assisted driving HAD service, of which the disclosedembodiments are a component thereof.

In a networked deployment, the computer system 500 may operate in thecapacity of a server or as a client user computer in a client-serveruser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 500 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a palmtop computer, a laptopcomputer, a desktop computer, a communications device, a wirelesstelephone, a landline telephone, a control system, a camera, a scanner,a facsimile machine, a printer, a pager, a personal trusted device, aweb appliance, a network router, switch or bridge, or any other machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. In some embodiments,the computer system 500 can be implemented using electronic devices thatprovide voice, video or data communication. Further, while a singlecomputer system 500 is illustrated, the term “system” shall also betaken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

As shown in FIG. 5, the computer system 500 may include a processor 502,for example a central processing unit (CPU), a graphics-processing unit(GPU), or both. The processor 502 may be a component in a variety ofsystems. For example, the processor 502 may be part of a standardpersonal computer or a workstation. The processor 502 may be one or moregeneral processors, digital signal processors, application specificintegrated circuits, field programmable gate arrays, servers, networks,digital circuits, analog circuits, combinations thereof, or other nowknown or later developed devices for analyzing and processing data. Theprocessor 502 may implement a software program, such as code generatedmanually (i.e., programmed).

The computer system 500 may include a memory 504 that can communicatevia a bus 508. The memory 504 may be a main memory, a static memory, ora dynamic memory. The memory 504 may include, but is not limited to,computer-readable storage media such as various types of volatile andnon-volatile storage media, including but not limited to random accessmemory, read-only memory, programmable read-only memory, electricallyprogrammable read-only memory, electrically erasable read-only memory,flash memory, magnetic tape or disk, optical media and the like. In someembodiments, the memory 504 includes a cache or random access memory forthe processor 502. In alternative embodiments, the memory 504 isseparate from the processor 502, such as a cache memory of a processor,the system memory, or other memory. The memory 504 may be an externalstorage device or database for storing data. Examples include a harddrive, compact disc (CD), digital video disc (DVD), memory card, memorystick, floppy disc, universal serial bus (USB) memory device, or anyother device operative to store data. The memory 504 is operable tostore instructions executable by the processor 502. The functions, actsor tasks illustrated in the figures or described herein may be performedby the programmed processor 502 executing the instructions 512 stored inthe memory 504. The functions, acts or tasks are independent of theparticular type of instructions set, storage media, processor orprocessing strategy and may be performed by software, hardware,integrated circuits, firm-ware, micro-code and the like, operating aloneor in combination. Likewise, processing strategies may includemultiprocessing, multitasking, parallel processing and the like.

As shown in FIG. 5, the computer system 500 may further include adisplay unit 514, such as a liquid crystal display (LCD), an organiclight emitting diode (OLED), a flat panel display, a solid statedisplay, a cathode ray tube (CRT), a projector, a printer or other nowknown or later developed display device for outputting determinedinformation. The display 514 may act as an interface for the user to seethe functioning of the processor 502, or specifically as an interfacewith the software stored in the memory 504 or in the drive unit 506.

Additionally, as shown in FIG. 5, the computer system 500 may include aninput device 516 configured to allow a user to interact with any of thecomponents of system 500. The input device 516 may be a number pad, akeyboard, or a cursor control device, such as a mouse, or a joystick,touch screen display, remote control or any other device operative tointeract with the system 500.

In some embodiments, as shown in FIG. 5, the computer system 500 mayalso include a disk or optical drive unit 506. The disk drive unit 506may include a computer-readable medium 510 in which one or more sets ofinstructions 512 (e.g., software) can be embedded. Further, theinstructions 512 may embody one or more of the methods or logic asdescribed herein. In some embodiments, the instructions 512 may residecompletely, or at least partially, within the memory 504 and/or withinthe processor 502 during execution by the computer system 500. Thememory 504 and the processor 502 also may include computer-readablemedia as described above.

The present teachings contemplate a computer-readable medium thatincludes instructions 512 or receives and executes instructions 512responsive to a propagated signal, so that a device connected to anetwork 520 can communicate voice, video, audio, images or any otherdata over the network 520. Further, the instructions 512 may betransmitted or received over the network 520 via a communicationinterface 518. The communication interface 518 may be a part of theprocessor 502 or may be a separate component. The communicationinterface 518 may be created in software or may be a physical connectionin hardware. The communication interface 518 is configured to connectwith a network 520, external media, the display 514, or any othercomponents in system 500, or combinations thereof. The connection withthe network 520 may be a physical connection, such as a wired Ethernetconnection or may be established wirelessly as discussed below.Likewise, the additional connections with other components of the system500 may be physical connections or may be established wirelessly.

The network 520 may include wired networks, wireless networks, orcombinations thereof. The wireless network may be a cellular telephonenetwork, an 802.11, 802.16, 802.20, or WiMax network. Further, thenetwork 520 may be a public network, such as the Internet, a privatenetwork, such as an intranet, or combinations thereof, and may utilize avariety of networking protocols now available or later developedincluding, but not limited to TCP/IP based networking protocols.

Embodiments of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Embodiments ofsubject matter described in this specification can be implemented as oneor more computer program products, for example, one or more modules ofcomputer program instructions encoded on a computer-readable medium forexecution by, or to control the operation of, data processing apparatus.While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein. The computer-readablemedium can be a machine-readable storage device, a machine-readablestorage substrate, a memory device, or a combination of one or more ofthem. The term “data processing apparatus” encompasses all apparatuses,devices, and machines for processing data, including but not limited to,by way of example, a programmable processor, a computer, or multipleprocessors or computers. The apparatus can include, in addition tohardware, code that creates an execution environment for the computerprogram in question (e.g., code that constitutes processor firmware, aprotocol stack, a database management system, an operating system, or acombination thereof).

In some embodiments, the computer-readable medium can include asolid-state memory such as a memory card or other package that housesone or more non-volatile read-only memories. Further, thecomputer-readable medium can be a random access memory or other volatilere-writable memory. Additionally, the computer-readable medium caninclude a magneto-optical or optical medium, such as a disk or tapes orother storage device to capture carrier wave signals such as a signalcommunicated over a transmission medium. A digital file attachment to ane-mail or other self-contained information archive or set of archivesmay be considered a distribution medium that is a tangible storagemedium. Accordingly, the present teachings are considered to include anyone or more of a computer-readable medium or a distribution medium andother equivalents and successor media, in which data or instructions maybe stored.

In some embodiments, dedicated hardware implementations, such asapplication specific integrated circuits, programmable logic arrays, andother hardware devices, can be constructed to implement one or more ofthe methods described herein. Applications that may include theapparatus and systems of various embodiments can broadly include avariety of electronic and computer systems. One or more embodimentsdescribed herein may implement functions using two or more specificinterconnected hardware modules or devices with related control and datasignals that can be communicated between and through the modules, or asportions of an application-specific integrated circuit. Accordingly, thepresent system encompasses software, firmware, and hardwareimplementations.

In some embodiments, the methods described herein may be implemented bysoftware programs executable by a computer system. Further, in someembodiments, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

Although the present teachings describe components and functions thatmay be implemented in particular embodiments with reference toparticular standards and protocols, the present invention is not limitedto such standards and protocols. For example, standards for Internet andother packet switched network transmission (e.g., TCP/IP, UDP/IP, HTML,HTTP, HTTPS) represent examples of the state of the art. Such standardsare periodically superseded by faster or more efficient equivalentshaving essentially the same functions. Accordingly, replacementstandards and protocols having the same or similar functions as thosedisclosed herein are considered equivalents thereof.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a standalone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described herein can be performed by oneor more programmable processors executing one or more computer programsto perform functions by operating on input data and generating output.The processes and logic flows can also be performed by, and apparatuscan also be implemented as, special purpose logic circuitry, forexample, an FPGA (field programmable gate array) or an ASIC (applicationspecific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The main elements of a computer are aprocessor for performing instructions and one or more memory devices forstoring instructions and data. Generally, a computer will also include,or be operatively coupled to receive data from or transfer data to, orboth, one or more mass storage devices for storing data, for example,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, for example, a mobile telephone, a personal digitalassistant (PDA), a mobile audio player, a Global Positioning System(GPS) receiver, to name just a few. Computer-readable media suitable forstoring computer program instructions and data include all forms of nonvolatile memory, media and memory devices, including but not limited to,by way of example, semiconductor memory devices (e.g., EPROM, EEPROM,and flash memory devices); magnetic disks (e.g., internal hard disks orremovable disks); magneto optical disks; and CD ROM and DVD-ROM disks.The processor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

To provide for interaction with a user, some embodiments of subjectmatter described herein can be implemented on a device having a display,for example a CRT (cathode ray tube) or LCD (liquid crystal display)monitor, for displaying information to the user and a keyboard and apointing device, for example a mouse or a trackball, by which the usercan provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. By way of example, feedbackprovided to the user can be any form of sensory feedback (e.g., visualfeedback, auditory feedback, or tactile feedback); and input from theuser can be received in any form, including but not limited to acoustic,speech, or tactile input.

Embodiments of subject matter described herein can be implemented in acomputing system that includes a back-end component, for example, as adata server, or that includes a middleware component, for example, anapplication server, or that includes a front end component, for example,a client computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, for example, a communication network. Examples ofcommunication networks include but are not limited to a local areanetwork (LAN) and a wide area network (WAN), for example, the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the invention or of what may beclaimed, but rather as descriptions of features specific to particularembodiments. Certain features that are described in this specificationin the context of separate embodiments can also be implemented incombination in a single embodiment. Conversely, various features thatare described in the context of a single embodiment can also beimplemented in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination can in some cases be excisedfrom the combination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings and describedherein in a particular order, this should not be understood as requiringthat such operations be performed in the particular order shown or insequential order, or that all illustrated operations be performed, toachieve desirable results. In certain circumstances, multitasking andparallel processing may be advantageous. Moreover, the separation ofvarious system components in the embodiments described above should notbe understood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 CFR§1.72(b) and is submitted with the understanding that it will not beused to interpret or limit the scope or meaning of the claims. Inaddition, in the foregoing Detailed Description, various features may begrouped together or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

It is to be understood that the elements and features recited in theappended claims may be combined in different ways to produce new claimsthat likewise fall within the scope of the present invention. Thus,whereas the dependent claims appended below depend from only a singleindependent or dependent claim, it is to be understood that thesedependent claims can, alternatively, be made to depend in thealternative from any preceding claim—whether independent ordependent—and that such new combinations are to be understood as forminga part of the present specification.

The foregoing detailed description and the accompanying drawings havebeen provided by way of explanation and illustration, and are notintended to limit the scope of the appended claims. Many variations inthe presently preferred embodiments illustrated herein will be apparentto one of ordinary skill in the art, and remain within the scope of theappended claims and their equivalents.

We claim:
 1. A method comprising: receiving telematics sensor data at avehicle data collector; initiating a transmission of the telematicssensor data to a cloud server; determining whether the transmission ofthe telematics sensor data to the cloud server meets a predeterminedlatency threshold; and instructing the cloud server, in response to thetransmission meeting the predetermined latency threshold, to execute adriving application for an autonomous driving command.
 2. The method ofclaim 1, further comprising: anonymizing the telematics sensor databefore the transmission.
 3. The method of claim 1, wherein a firstvehicle comprises the vehicle data collector, and wherein the autonomousdriving command is associated with a second vehicle.
 4. The method ofclaim 1, further comprising: collecting the telematics sensor data atone or more sensors.
 5. The method of claim 4, wherein the one or moresensors include differential global positioning system (GPS), windshieldwiping sensors, laser sensors, light sensors, camera sensors, microphonesensors, shift sensors, pedal sensors, lever sensors, brake sensors,speed sensors, acceleration sensors, headlamp sensors, steering wheelsensors, or a combination thereof.
 6. The method of claim 1, furthercomprising: compressing the telematics sensor data before thetransmission.
 7. The method of claim 1, further comprising: envelopingthe telematics sensor data to a predetermined format before thetransmission.
 8. The method of claim 1, wherein the predeterminedlatency threshold is assigned to the driving application.
 9. The methodof claim 1, wherein the cloud server includes a plurality of analysisloops for the telematics sensor data.
 10. The method of claim 9, whereinat least one analysis loop corresponds to real world reference data froma three dimensional map.
 11. The method of claim 9, wherein at least oneanalysis loop corresponds to real time environmental data indicative ofa status of an environment of the vehicle.
 12. The method of claim 9,wherein at least one analysis loop corresponds to personalized driving.13. An apparatus comprising: at least one processor; and at least onememory including computer program code for one or more programs, the atleast one memory and the computer program code configured to, with theat least one processor, cause the apparatus to perform at least thefollowing: receiving telematics sensor data at a vehicle data collector;initiating a transmission of the telematics sensor data to a cloudserver; determining whether the transmission of the telematics sensordata to the cloud server meets a predetermined latency threshold; andinstructing the cloud server, in response to the transmission meetingthe predetermined latency threshold, to execute a driving applicationfor an autonomous driving command.
 14. The apparatus of claim 13, the atleast one memory and the computer program code configured to, with theat least one processor, cause the apparatus to perform: anonymizing thetelematics sensor data before the transmission.
 15. The apparatus ofclaim 13, wherein a first vehicle comprises the vehicle data collector,and wherein the autonomous driving command is associated with a secondvehicle.
 16. The apparatus of claim 13, the at least one memory and thecomputer program code configured to, with the at least one processor,cause the apparatus to perform: compressing the telematics sensor databefore the transmission.
 17. The apparatus of claim 13, the at least onememory and the computer program code configured to, with the at leastone processor, cause the apparatus to perform: enveloping the telematicssensor data to a predetermined format before the transmission.
 18. Theapparatus of claim 13, wherein the predetermined latency threshold isassigned to the driving application.
 19. The method of claim 1, whereinthe cloud server executes a plurality of analysis loops for thetelematics sensor data, the plurality of analysis loops including afirst analysis loop corresponds to real world reference data from athree dimensional map, a second analysis loop corresponds to real timeenvironmental data indicative of a status of an environment of thevehicle, and a third analysis loop corresponds to personalized driving.20. A non-transitory computer readable medium including instructionsthat when executed cause a processor to perform: process telematicssensor data; initiating a transmission of the telematics sensor data toa cloud server; determining whether the transmission of the telematicssensor data to the cloud server meets a predetermined latency threshold;and instructing the cloud server, in response to the transmissionmeeting the predetermined latency threshold, to execute a drivingapplication for an autonomous driving command.